During the 2012 Deep Convective Clouds and Chemistry (DC3) experiment the National Science Foundation/National Center for Atmospheric Research Gulfstream V (GV) aircraft sampled the upper anvils of two storms that developed in eastern Colorado on 6 June 2012. A cloud particle imager (CPI) mounted on the GV aircraft recorded images of ice crystals at altitudes of 12.0 to 12.4 km and temperatures (T ) from-61 to-55 °C. A total of 22 393 CPI crystal images were analyzed, all with maximum dimension (Dmax) < 433 μ m and with an average Dmax of 80.7± 45.4 μ m. The occurrence of well-defined pristine crystals (e.g., columns and plates) was less than 0.04% by number. Single frozen droplets and frozen droplet aggregates (FDAs) were the dominant habits with fractions of 73.0% (by number) and 46.3%(by projected area), respectively. The relative frequency of occurrence of single frozen droplets and FDAs depended on temperature and position within the anvil cloud. A new algorithm that uses the circle Hough transform technique was developed to automatically identify the number, size, and relative position of element frozen droplets within FDAs. Of the FDAs, 42.0% had two element frozen droplets with an average of 4.7±5.0 element frozen droplets. The frequency of occurrence gradually decreased with the number of element frozen droplets. Based on the number, size, and relative position of the element frozen droplets within the FDAs, possible three-dimensional (3-D) realizations of FDAs were generated and characterized by two different shape parameters, the aggregation index (AI) and the fractal dimension (Df), that describe 3-D shapes and link to scattering properties with an assumption of spherical shape of element frozen droplets. The AI of FDAs decreased with an increase in the number of element frozen droplets, with larger FDAs with more element frozen droplets having more compact shapes. The Df of FDAs was about 1.20-1.43 smaller than that of black carbon (BC) aggregates (1.53-1.85) determined in previous studies. Such a smaller Df of FDAs indicates that FDAs have more linear chain-like branched shapes than the compact shapes of BC aggregates. Determined morphological characteristics of FDAs along with the proposed reconstructed 3-D representations of FDAs in this study have important implications for improving the calculations of the microphysical (e.g., fall velocity) and radiative (e.g., asymmetry parameter) properties of ice crystals in upper anvil clouds.
Bibliographical noteFunding Information:
The 2012 DC3 experiment investigated the impacts of deep midlatitude continental convective clouds on upper tropospheric chemistry and composition in the US Midwest (Barth et al., 2015). The National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV), the National Aeronautics and Space Administration (NASA) DC-8, and the Deutsches Zentrum für Luft-und Raumfahrt (DLR) Falcon aircraft were deployed during DC3.
Acknowledgements. This work was supported by funding from the National Science Foundation under grant no. AGS 12-13311 and from the Advanced Study Program (ASP) at the National Center for Atmospheric Research. The National Center for Atmospheric Research is sponsored by the National Science Foundation. Part of this work was completed while Greg M. McFarquhar was on sabbatical at NCAR. This research was supported by the National Strategic Project – Fine particle of the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), the Ministry of Environment (ME), and the Ministry of Health and Welfare (MOHW) (project no. NRF-2017M3D8A1092022). This study was also funded by the Korea Meteorological Administration Research and Development Program “Research and Development for KMA Weather, Climate, and Earth system Services Development of Application Technology on Atmospheric Research Aircraft” under (grant no. KMA2018-00222). We would like to acknowledge operational, technical, and scientific support provided by NCAR’s Earth Observing Laboratory, sponsored by the National Science Foundation.
© 2018 Author(s).
All Science Journal Classification (ASJC) codes
- Atmospheric Science